Canine and Feline Skin Cytology: A Comprehensive and Illustrated Guide to the Interpretation of Skin Lesions via Cytological Examination


Canine and Feline Skin Cytology: A Comprehensive and Illustrated Guide to the Interpretation of Skin Lesions via Cytological Examination

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Críticas “This book describes the principles of survival analysis gives examples of how it is applied and teaches how to put those principles to use to analyze data using R. … The intended audience includes students taking a master's level course in statistical theory and analysts who need to work with survival time data. … This is an excellent overview of the main principles of survival analysis and its applications with examples using R for the intended audience.” (Hemang B. Panchal Doody’s Book Reviews August 2016) Reseña del editor Applied Survival Analysis Using R covers the main principles of survival analysis gives examples of how it is applied and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data where the primary outcome is time to a specific event arise in many areas of biomedical research including clinical trials epidemiological studies and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation comparison of survivals of different groups proper accounting for censoring and truncation model variable selection and residual analysis.Because explaining survival analysis requires more advanced mathematics than many other statistical topics this book is organized with basic concepts and most frequently used procedures covered in earlier chapters with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis as well as a basic knowledge of calculus and the R system will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points shedding light on the application of survival analysis in a way that is useful for graduate students researchers and practitioners in biostatistics. Contraportada Applied Survival Analysis Using R covers the main principles of survival analysis gives examples of how it is applied and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data where the primary outcome is time to a specific event arise in many areas of biomedical research including clinical trials epidemiological studies and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation comparison of survivals of different groups proper accounting for censoring and truncation model variable selection and residual analysis.Because explaining survival analysis requires more advanced mathematics than many other statistical topics this book is organized with basic concepts and most frequently used procedures covered in earlier chapters with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis as well as a basic knowledge of calculus and the R system will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points shedding light on the application of survival analysis in a way that is useful for graduate students researchers and practitioners in biostatistics.Clearly illustrates concepts of survival analysis principles and analyzes actual survival data using R in addition to including an appendix with a basic introduction to ROrganized via basic concepts and most frequently used procedures with advanced topics toward the end of the book and in appendicesIncludes multiple original data sets that have not appeared in other textbooksDirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and prior to joining Rutgers was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies. Biografía del autor Dirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and prior to joining Rutgers was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies.

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